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Hey HN! I've always found it hard to keep up with the latest AI research, so I built Arxiv Feed! https://arxiv-feed.vercel.app/ It's basically a feed of AI research papers + a one-liner explaining what problem its solving, etc. You can also click on any paper to get a TL;DR. Right now, I've only indexed a few hundred large language model papers, but will expand to indexing AI papers in other topics. Thinking of also adding a way for people to up-vote/down-vote papers. Would love to hear any thoughts/feedback! :D Thanks!
2023 · arxiv-feed.vercel.app
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2023 · bulletpapers.ai
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As a grad student (and an ADHDer), I had trouble doing literature review systematically. To combat this, I made a website that finds similar papers using the meaning of the thing I am looking for. I used MixedBread's [^1] embedding model to generate vectors from the abstracts. I store and search similar vectors using Milvus [^2] and finally use Gradio [^3] to serve the frontend. I update the vector database weekly by pulling the metadata dataset from Kaggle [^4]. To speed up the search process on my free oracle instance, I binarise the embeddings and use Hamming distance as a metric. I would…
2024 · papermatch.mitanshu.tech
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Built an automated system to run a deep search of ArXiv and carefully find all the precise papers that exist on a complex topic. It's different from simple RAG because it searches, classifies, and adapts based on relevant papers it uncovers, and then continues until it finds every paper on a topic (trying to mimic the human research process). Benchmarked 10x higher accuracy and total retrieval compared to Google Scholar for a median search (whitepaper on website). Also knows when it is complete, and misses virtually nothing (< 3% or so, once it's converged). Website has a free trial and a…
2024 · app.undermind.ai
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I feel like LLMs can help me understand anything. However, after I get a summary, I can't dive in to parts that I find interesting; can't refer to original source easily and can't control context with chatbots. This is an attempt to solve for a complete knowledge consumption experience with AI . Please give me feedback!
Oct 2025 · kerns.ai
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As a researcher, I created SmartXiv to solve a problem I faced every day: keeping up with the overwhelming number of research papers uploaded to arXiv. With over 1000 new papers each day, finding the most relevant research was time-consuming and exhausting. I needed a smarter way to stay updated. What SmartXiv Does • Personalized Recommendations: Using advanced AI, SmartXiv analyzes your interests and sends you daily emails with research papers that align with your preferences. •Efficient Research: By curating the latest papers for you, SmartXiv saves you hours of research. • Fully…
2024 · smartxiv.com
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I made this, and it's fully open source so if someone wants to contribute here you have the url: https://github.com/Miguel07Alm/arxivtok. For this project I was inspired by https://wikitok.vercel.app.
2025 · arxivtok.vercel.app
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I’ve been frustrated with PDFs and found arXiv HTML lacking, so I built a fully interactive paper reader. Features: • Hover references, citations, equations • Light/dark mode • Auto-generated dependency graphs for definitions/lemmas/theorems • Table of contents that syncs with scroll • Highlighting + annotations • “Copy raw LaTeX” anywhere Featured paper: Video models are zero-shot learners and reasoners (Veo 3) https://www.sciencestack.ai/arxiv/2509.20328v2
Nov 2025 · sciencestack.ai
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Building a multi-agent system to analyze new AI research papers from 3 distinct perspectives: - Deep learning researcher agent: extract interesting deep learning methods that are related to paper - Theoretical mathematician agent: figure out theoretical mathematical concepts that are important in this paper and additional theoretical references that will be useful in understanding it - Skeptic agent: find unjustified assumptions that lack supporting evidence For this mvp, I used low-code agent platform StackAI (YC W23) and wrote about my process:…
2024 · stack-ai.com
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Hey HN! Over the weekend (leaning heavily on Opus 4.5) I wrote Jargon - an AI-managed zettelkasten that reads articles, papers, and YouTube videos, extracts the key ideas, and automatically links related concepts together. Demo video: https://youtu.be/W7ejMqZ6EUQ Repo: https://github.com/schoblaska/jargon You can paste an article, PDF link, or YouTube video to parse, or ask questions directly and it'll find its own content. Sources get summarized, broken into insight cards, and embedded for semantic search. Similar ideas automatically cluster together. Each…
Dec 2025 · github.com
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A fun, more informed way to stay up to date on AI research
Mar 2026 · airesearchatlas.com
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Daily curated AI frontiers, straight to your inbox
Jul 2026 · ttkxplorer.gumroad.com
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Hi HN, Would love your thoughts on Open Paper Digest. It’s a mobile feed that let’s you “doomscroll” through summaries of popular papers that were published recently. Backstory There’s a combination of factors lead me to build this: 1. Quality of content social media apps has decreased, but I still notice that it is harder than ever for me to stay away from these apps. 2. I’ve been saying for a while now that I should start reading papers to keep up with what’s going on in AI-world. Initially, I set out to build something solely for point 2. This version was more search-focussed, and…
Dec 2025 · openpaperdigest.com
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3d ago · aibriefs.news
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